Crossover

systematica.signals.crossover

run_crossover_1d_nb

run_crossover_1d_nb(
    model_output: numpy.ndarray,
    long_entries: float,
    long_exits: float,
    short_entries: float,
    short_exits: float,
    clean: bool = True,
) ‑> systematica.signals.base.Signals

Compute 1-dimensional crossover trading signals.

Determines long and short entry/exit signals based on one-dimensional crossover conditions.

Parameters:

Name	Type	Default	Description
model_output	ndarray	--	A 1D array representing model predictions.
long_entries	float	--	Values for detecting long entry crossovers.
long_exits	float	--	Values for detecting long exit crossovers.
short_entries	float	--	Values for detecting short entry crossovers.
short_exits	float	--	Values for detecting short exit crossovers.

Returns:

Type	Description
Signals	A Signals object containing crossover-based signals.

run_crossover_nb

run_crossover_nb(
    model_output: numpy.ndarray,
    long_entries: float,
    long_exits: float,
    short_entries: float,
    short_exits: float,
    clean: bool = True,
) ‑> systematica.signals.base.Signals

Compute 2-dimensional crossover trading signals.

Determines long and short entry/exit signals based on two-dimensional crossover conditions.

Parameters:

Name	Type	Default	Description
model_output	ndarray	--	A 2D array representing model predictions.
long_entries	float	--	Values for detecting long entry crossovers.
long_exits	float	--	Values for detecting long exit crossovers.
short_entries	float	--	Values for detecting short entry crossovers.
short_exits	float	--	Values for detecting short exit crossovers.
clean	bool	to	True Clean signals. Defaults to True.

Returns:

Type	Description
Signals	A Signals object containing crossover-based signals.